The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Improving performance of cooling systems and controlling such cooling systems is rapidly gaining attention as the cooling needs for various facilities, in particular data centers, continue to grow in size. In particular, with a chilled water (“CW”) cooling system, a number of components operate to remove heat from a load, where the load may be created by a wide variety of different types of devices. In one example the load may be heat which is generated within data centers by dozens, hundreds or thousands of servers and other IT and/or network equipment. The basic CW cooling system may be understood, in one example, as including one or more chillers, one or more CW pumps, a bypass, one or more cooling tower pumps, one or more cooling towers, makeup water filtration controls, one or more variable frequency drives (VFDs) with controls, and associated piping connecting the aforementioned components. The performance and/or equipment set points associated with any one or more of these devices can have a bearing on the performance output of individual components and respectively the entire CW system during transition and balance. Presently there is no known system which is able to use the known information, performance abilities or performance curves of various ones of the components of a CW system to model how various important performance parameters of the CW system, such as total gallons per minute (GPM), temperature differential (ΔT) and SCWT (Supply Chilled Water Temperature) are likely to be affected if varying equipment set points are applied to one or more of the components of the CW system. Moreover, there is no way to be able to predict how a performance change (or user/system changed set point) for one specific component may affect operation of one or more of the other components of the system that may be receiving the direct or indirect output from the specific component.